Ernesto Araya — accepted AI-conference papers

2026

Random Spiking Neural Networks are Stable and Spectrally Simple

Massimiliano Datres, Ernesto Araya, Gitta Kutyniok

ICLR 2026poster

Spiking neural networks (SNNs) are a promising paradigm for energy-efficient computation, yet their theoretical foundations—especially regarding stability and robustness—remain limited compared to artificial neural networks. In this work, we study discrete-time leaky integrate-and-fire (LIF) SNNs th…

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2025

Time to Spike? Understanding the Representational Power of Spiking Neural Networks in Discrete Time

Duc Anh Nguyen, Ernesto Araya, Adalbert Fono, Gitta Kutyniok

ICML 2025poster

Recent years have seen significant progress in developing spiking neural networks (SNNs) as a potential solution to the energy challenges posed by conventional artificial neural networks (ANNs). However, our theoretical understanding of SNNs remains relatively limited compared to the ever-growing bo…

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